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COVID-19 Identification on Chest X-rays with Deep Learning Technique
Lecture Notes on Data Engineering and Communications Technologies ; 91:113-123, 2022.
Artigo em Inglês | Scopus | ID: covidwho-1540199
ABSTRACT
The COVID-19 infection has firmly affected all nations globally. COVID-19 disease is a lung infection by the novel CORONA virus. The present study aims to develop a binary classification deep neural network that identifies the COVID-19 disease on chest X-ray scans. The proposed model divides the chest X-rays is two classes;one is a normal chest X-ray or the other is covid infected. The model has utilized the benefit of the transfer learning method and implemented the ResNet-50 pre-trained model as the backbone model. 1200 chest X-rays have been used to conduct this study while the achieved accuracy is 97.92%. The proposed model also manifests the effect of deep learning techniques in the medical imaging domain. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Texto completo: Disponível Coleções: Bases de dados de organismos internacionais Base de dados: Scopus Idioma: Inglês Revista: Lecture Notes on Data Engineering and Communications Technologies Ano de publicação: 2022 Tipo de documento: Artigo

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Texto completo: Disponível Coleções: Bases de dados de organismos internacionais Base de dados: Scopus Idioma: Inglês Revista: Lecture Notes on Data Engineering and Communications Technologies Ano de publicação: 2022 Tipo de documento: Artigo